Procedural outline

Turn on machines / heaters. Put mice in tailcuff room and let the room and mice acclimate to appropriate temperature for ~30-60 mins. Then, check cuffs for leaks. Put mice into restraints and perform 5 acclimation cycles + 20 recorded cycles.

When placing mice into restraints,
1. Quickly place nose cuff on to avoid letting them turn around in the restraint
2. Make sure that you can see them breathing…
3. Maximize tightness of fit and breathing

Metadata Analysis

This workbook is set up to analyze two groups of mice! Just run and enjoy (you’ll probably need to change out drug names…)

Metadata
group Specimen Name Notch DOB Old Cage ID New Cage ID Status Date of death Machine ID Average body weight (g)
sorafenib M1 NN 2021-01-29 643256 655610 Alive NA 1 27.05000
vehicle M2 DR 2021-01-28 643256 655610 Alive NA 1 21.63333
vehicle M3 RN 2021-01-29 643256 655610 Alive NA 1 23.75000
sorafenib M4 LN 2021-01-29 643256 655611 Alive NA 1 27.43333
sorafenib M5 BN 2021-01-29 643256 655611 Alive NA 1 25.23333
vehicle M6 NN 2021-02-01 643259 655612 Alive NA 2 25.75000
vehicle M7 RN 2021-02-01 643259 655612 Alive NA 2 25.41667
sorafenib M8 BN 2021-02-01 643259 655612 Alive NA 2 25.98333
sorafenib M9 LN 2021-02-01 643259 655613 Alive NA 2 23.88333
sorafenib M10 DR 2021-02-01 643259 655613 Alive NA 2 24.78333

Inspect accepted cycles and changes in mouse body weight over time

### Average animal body weight

Animal body weight change over time

Blood Pressure Data Analysis

Filtering out days that had less than ‘x’ cycles

Removed days/Specimens with less than 5 cycles:
Specimen Name Date group # cycles reason
M7 2021-05-10 vehicle 4 Low cycle count

Removing outliers

Detect outliers BP measurements using boxplot methods. Boxplots are a popular and an easy method for identifying outliers. There are two categories of outlier: (1) outliers and (2) extreme points. Values above Q3 + 2xIQR or below Q1 - 2xIQR are considered as outliers. Q1 and Q3 are the first and third quartile, respectively. IQR is the interquartile range (IQR = Q3 - Q1). This method is more robust than STDEV based outlier detection because outliers can skew the mean and STDEV of a sample.

Here, outliers are nominated based on daily blood pressure recordings, so as to not throw out data on treatment days when the blood pressure is expected to rise above the average.

Additionally, we remove mice that are too ‘volatile’ after trianing period has finished.

Plot the data over time and visualize the variance per day, per sample with boxplots, over all days

Pilot 1 | sorafenib 30 mg/kg/d

Dates
Phase first last date_range Number of Days
training 2021-05-01 2021-05-06 2021-05-01 to 2021-05-06 6
vehicle 2021-05-07 2021-05-10 2021-05-07 to 2021-05-10 4
treatment 2021-05-11 2021-05-19 2021-05-11 to 2021-05-19 9

Assess BP of randomly assigned groups before getting treatment

3-day rolling average

Take the last 3-days of an interval and average them for more realistic averages

Time-series data

For completeness, here is the time series data of each mouse across each Phase of the experiment:

Time-series diff by individual mouse from vehicle average to end of treatment

Time-series diff by group

These are the average blood pressures of each mice across each Phase of the experiment

Booklet usage instructions

Download excel data after finishing the experiments onto thumb drive

Copy the data into a master excel file with two sheets, making sure that there’s only one header (at the very top of the page).

  1. You’ll need to add in two columns manually to this master sheet: Date and Phase. Phase can take one of 4 values: “training”, “baseline”, “vehicle”, “treatment”. Training data ultimately gets removed, but included in the data sheet for completeness. First sheet should look like this:
    Metadata
    Specimen Name Systolic Mean Rate Cycle # Date Phase
    M1 84 64 505 7 2021-05-01 training
    M1 90 74 628 8 2021-05-01 training
    M1 88 73 786 9 2021-05-01 training
    M1 94 76 686 10 2021-05-01 training
    M1 91 72 684 11 2021-05-01 training
    M1 92 73 689 12 2021-05-01 training
  2. Second sheet should be created manually based on your mice. Fill in the various fields.
    Metadata
    Specimen Name Notch DOB Old Cage ID New Cage ID Body weight (g) Date Status Date of death Machine ID
    M1 NN 2021-01-29 643256 655610 27.1 2021-04-12 Alive NA 1
    M2 DR 2021-01-28 643256 655610 21.6 2021-04-12 Alive NA 1
    M3 RN 2021-01-29 643256 655610 23.5 2021-04-12 Alive NA 1
    M4 LN 2021-01-29 643256 655611 27.4 2021-04-12 Alive NA 1
    M5 BN 2021-01-29 643256 655611 24.8 2021-04-12 Alive NA 1
    M6 NN 2021-02-01 643259 655612 26.7 2021-04-12 Alive NA 2
    M7 RN 2021-02-01 643259 655612 25.9 2021-04-12 Alive NA 2
    M8 BN 2021-02-01 643259 655612 26.0 2021-04-12 Alive NA 2
    M9 LN 2021-02-01 643259 655613 24.4 2021-04-12 Alive NA 2
    M10 DR 2021-02-01 643259 655613 25.0 2021-04-12 Alive NA 2